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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Relativistic mean-field theories for neutron-star physics based on chiral effective field theory

We describe and implement a procedure for determining the couplings of a relativistic mean-field theory (RMFT) that is optimized for application to neutron star phenomenology. In the standard RMFT approach, the couplings are constrained by comparing the theory's predictions for symmetric matter at saturation density with measured nuclear properties. The theory is then applied to neutron stars which consist of neutron-rich matter at densities ranging up to several times saturation density, which allows for additional astrophysical constraints. In our approach, rather than using the RMFT to extrapolate from symmetric to neutron-rich matter and from finite-sized nuclei to uniform matter, we fit the RMFT to properties of uniform pure neutron matter obtained from chiral effective field theory. Chiral effective field theory incorporates the experimental data for nuclei in the framework of a controlled expansion for nuclear forces valid at nuclear densities and enables us to account for theoretical uncertainties when fitting the RMFT. We construct four simple RMFTs that span the uncertainties provided by chiral effective field theory for neutron matter, and are consistent with current astrophysical constraints on the equation of state. Lastly, our RMFTs can be used to model the properties of neutron-rich matter across the vast range of densities and temperatures encountered in neutron stars and their mergers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Predicting High Energy Arcing Fault Zones of Influence for Aluminum Using an Arc Flash Modeling Approach: Evaluation of a model bias, uncertainty, parameter sensitivity and zone of influence estimation

This report documents the development of an arc flash hazard model to calculate the incident energy and zone of influence from high energy arcing faults involving aluminum. The NRC has identified the potential for (HEAFs) involving aluminum to increase the damage zone beyond what is currently postulated in fire probabilistic risk assessment (PRA) methodologies. To estimate the hazard from HEAFs involving aluminum an arc flash model was developed. Differences between the initial model and nuclear power plant (NPP) fire PRA scenarios were identified. Modification of the initial model established from existing literature and test data was used to minimize these differences. The developed model was evaluated against NRC datasets to understand the model prediction and relative uncertainties. Finally, a range of fire PRA zone of influences (ZOI) were developed based on the developed model, target fragility estimates and update HEAF PRA methodology. The results were developed to support an NRC LIC-504 evaluation in tandem with other modeling efforts. The report documents the effort and provides a reference for any future advancements in arc flash modeling.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

A decay database of coincident γ–γ and γ–X -ray branching ratios for in-field spectroscopy applications

Current fieldable spectroscopy techniques often use single detector systems heavily impacted by interferences from intense background radiation fields. These effects result in low-confidence measurements that can lead to misinterpretation of the collected spectrum. To help improve interpretation of the fission products and short-lived radionuclides produced in a composite sample, a coincidence-database is being developed in support of a robust portable and X-ray coincidence detector system concurrently under development at the Pacific Northwest National Laboratory for in-field deployment. Hitherto, no database exists containing coincident γ–γ and γ–X-ray branching-ratio intensities on an absolute scale that will greatly enhance isotopic identification for in-field applications. As part of this project, software has been developed to parse all radioactive-decay data sets from the Evaluated Nuclear Structure Data File (ENSDF) archive to enable translation into a more useful JavaScript Object Notation (JSON) formats that more readily supports query-based data manipulation. The coincident database described in this work is the first of its kind and contains coincidence γ–γ and γ–X-ray intensities and their corresponding uncertainties, together with auxiliary metadata associated with each decay data set. The new JSON format provides a convenient and portable means of data storage that can be imported into analysis frameworks with relatively low overhead allowing for meaningful comparison with measured data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Global analyses of nuclear PDFs with heavy-quark and neutrino data

We discuss the two most recent global analyses of nuclear parton distribution functions within the nCTEQ approach. LHC data on $W/Z$-boson, single-inclusive hadron and heavy quark/quarkonium production are shown to not only significantly reduce the gluon uncertainty down to $x\geq10^{-5}$, but to also influence the strange quark density. The latter is further constrained by neutrino deep-inelastic scattering and charm dimuon production data, whose consistency with neutral-current experiments is also re-evaluated.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Exploiting 20 Ne Isotopes for Precision Characterizations of Collectivity in Small Systems

Whether or not femto-scale droplets of quark-gluon plasma (QGP) are formed in so-called small systems at high-energy colliders is a pressing question in the phenomenology of the strong interaction. For proton-proton or proton-nucleus collisions the answer is inconclusive due to the large theoretical uncertainties plaguing the description of these processes. While upcoming data on collisions of 16 O nuclei may mitigate these uncertainties in the near future, here we demonstrate the unique possibilities offered by complementing 16 O + 16 O data with collisions of 20 Ne ions. We couple both nuclear lattice effective field theory (NLEFT) and projected generator coordinate method (PGCM) ab initio descriptions of the structure of 20 Ne and 16 O to hydrodynamic simulations of 16 O + 16 O and 20 Ne + 20 Ne collisions at high energy. We isolate the imprints of the bowling-pin shape of 20 Ne on the collective flow of hadrons, which can be used to perform quantitative tests of the hydrodynamic QGP paradigm. In particular, we predict that the elliptic flow of 20 Ne + 20 Ne collisions is enhanced by as much as 1.174⁢(8) stat ⁢(31) syst for NLEFT and 1.139⁢(6) stat ⁢(39) syst for PGCM relative to 16 O + 16 O collisions for the 1% most central events. At the same time, theoretical uncertainties largely cancel when studying relative variations of observables between two systems. This demonstrates a method based on experiments with two light-ion species for precision characterizations of the collective dynamics and its emergence in a small system.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Analytic insights on the information content of new observables

Uncertainty quantification has emerged as a rapidly growing field in nuclear science. Theoretical predictions of physical observables often involve extrapolations to regions that are poorly constrained by laboratory experi- ments and astrophysical observations. Without properly quantified theoretical errors, such model predictions are of limited value. Also, one often deals with theoretical constructs that involve fundamental quantities that are not accessible to experiment or observation. Particularly relevant in this context is the pressure of pure neutron matter. Furthermore, in this Rapid Communication, we develop an analytic framework to answer the question of “How can new data reduce uncertainties of current theoretical models?” Simple and insightful expressions are obtained to quantify the impact of one or two new observables on theoretical uncertainties in two critical quantities: The slope of the symmetry energy at saturation density and the pressure of pure neutron matter at twice nuclear matter saturation density.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Probabilistic Programming for Transportable Source Characterization and Uncertainty Quantification of the North Korean Nuclear Tests 2006–2017

Here, we introduce a transportable technique to determine the yield and depth of burial (DOB) from seismic source spectra of underground nuclear explosions. We demonstrate this technique on the six declared North Korean nuclear tests. This approach derives source spectra in absolute units from regional phase (Pg) amplitudes by correcting the observations for geometric spreading, attenuation, and site amplification. We couple the source spectra and explosion source models with a probabilistic programming framework that integrates deep learning techniques and Bayesian modeling. This approach permits the exchange of information across various data categories to quantify both the data and model uncertainty. This technique stands out as an innovative use of broad‐area propagation models, making it transportable across various geologic settings. This method proves to be effective in scenarios with diverse and/or limited observational data, even when the source depth is unknown. We present new independent estimates of absolute yield and DOB that are consistent with the prior assessments, underscoring the potential of this method in enhancing transportable nuclear explosion monitoring capabilities.

58 GEOSCIENCES↗
DOE OSTI2023

Nuclear recoil response of liquid xenon and its impact on solar 8B neutrino and dark matter searches

Knowledge of the ionization and scintillation responses of liquid xenon (LXe) to nuclear recoils is crucial for LXe-based dark matter experiments. Current calibrations carry large uncertainties in the low-energy region below ∼3 keV nr where signals from dark matter particles of <10 GeV/c 2 masses are expected. The coherent elastic neutrino-nucleus scattering (CE ν NS) by solar 8 B neutrinos also results in a continuum of nuclear recoil events below 3.0 keV nr (99% of events), which further complicates low-mass dark matter searches in LXe experiments. In this paper, we describe a method to quantify the uncertainties of low-energy LXe responses using published calibration data, followed by case studies to evaluate the impact of yield uncertainties on 8 B searches and low-mass dark matter sensitivity in a typical ton-scale LXe experiment. We conclude that naively omitting yield uncertainties leads to overly optimistic limits by factor ∼2 for a 6 GeV WIMP mass. Future nuclear recoil light yield calibrations could allow experiments to recover this sensitivity and also improve the accuracy of solar 8 B flux measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Theoretical uncertainty quantification for heavy-ion fusion

Despite recent advances and focus on rigorous uncertainty quantification for microscopic models of quantum many-body systems, the uncertainty on the dynamics of those systems has been underexplored. To address this, we have used time-dependent Hartree-Fock to examine the model uncertainty for a collection of low-energy, heavy-ion fusion reactions. Fusion reactions at near-barrier energies represent a rich test-bed for the dynamics of quantum many-body systems owing to the complex interplay of collective excitation, transfer, and static effects that determine the fusion probability of a given system. The model uncertainty is sizable for many of the systems studied and the primary contribution arises from static properties that are ill-constrained, such as the neutron radius of neutron-rich nuclei. Furthermore, these large uncertainties motivate the use of information from reactions to better constrain existing models and to infer static properties from reaction data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

RAVEN User Manual

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused to- ward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assessment capability to RELAP-7, currently under development at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with soft- ware such as RELAP5-3D, etc. The aim of this document is the explanation of the input requirements, focalizing on the input structure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

SMR safety through HTTF modeling and benchmark efforts for code validation for gas-cooled reactor applications

Accurate modeling and simulation tools for thermal-hydraulics calculations are a key element needed to design and license new advanced reactors including Small Modular Reactors (SMR) and Microreactors. Uncertainties in modeling and simulation can have significant safety and economic implications. The High Temperature Test Facility (HTTF) at Oregon State University (OSU) is a scaled integral effects experiment designed to investigate transient behavior in high-temperature gas-cooled prismatic-block nuclear reactors. High-quality measurement data is available from the HTTF that is suitable for a thermal-hydraulics code validation benchmark for gas-cooled reactor simulations. Here, this paper summarizes individual HTTF modeling efforts to date for tool validation at Idaho National Laboratory (INL), Argonne National Laboratory (ANL), Oregon State University (OSU) and Canadian Nuclear Laboratories (CNL) using system thermal-hydraulics codes, Computational Fluid Dynamics (CFD) codes and system-CFD code couplings. Also, the paper introduces the ongoing OECD Nuclear Energy Agency (NEA) High Temperature Gas Reactor Thermal-Hydraulics (HTGR T/H) benchmark that allows for better comparisons of results between different international modeling teams. The benchmark provides well defined computational problems that include code-to-code comparisons and comparisons to measured data. These problems provide an avenue for quantifying accuracy and identifying sources of uncertainty in thermal-hydraulics calculations, including in measured thermophysical properties, as part of validation for gas-cooled reactor simulation tools.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2024

Uncertainty quantification of mass models using ensemble Bayesian model averaging

Developments in the description of the masses of atomic nuclei have led to various nuclear mass models that provide predictions for masses across the whole chart of nuclides. These mass models play an important role in understanding the synthesis of heavy elements in the rapid neutron capture ( r ) process. However, it is still a challenging task to estimate the size of uncertainty associated with the predictions of each mass model. In this work, a method called ensemble Bayesian model averaging (EBMA) is introduced to quantify the uncertainty of one-neutron separation energies (S 1 n ) which are directly relevant in the calculations of r -process observables. Here, this Bayesian method provides a natural way to perform model averaging, selection, and uncertainty quantification, by combining the mass models as a mixture of normal distributions whose parameters are optimized against the experimental data, employing the Markov chain Monte Carlo method using the no-u-turn sampler. The EBMA model optimized with all the experimental S 1 n from the AME2003 nuclides are shown to provide reliable uncertainty estimates when tested with the new data in the AME2020.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Integrating Data Sources for Improved Safeguards and Accountancy of Electrochemical Fuel Reprocessing Systems. Final Report

Electrochemical reprocessing (also commonly known as “pyroprocessing”) of used nuclear fuel is an alternative to aqueous reprocessing that confers a number of advantages, including the ability to process more recently-discharged fuel, smaller resultant waste volumes, and the lack of isolation of plutonium in the product stream. While electrochemical reprocessing systems have seen a significant research and development effort, nuclear safeguards and security of these systems remains under-developed, particularly given the significant differences in operating environment and process flowsheet compared with established aqueous methods. Objective 4 of DOE’s nuclear energy research and development activities in Nuclear Energy Research and Development Roadmap is: “Understand and minimize the risks of nuclear proliferation and terrorism.” Material Control & Accountancy (MC&A) programs at nuclear processing plants deter and detect theft and diversion of nuclear material by both outside and inside adversaries. Empirical modeling and data analytics of online measurements and state indicators can improve the timeliness of detection and reduce the uncertainty in accountancy measures. To support the development and demonstration of such methods, data are needed that capture expected measurement values collected throughout electrochemical reprocessing facilities. A review of the available literature of current research in measurements for electrochemical reprocessing systems identified twenty-two candidate measurement methodologies, which characterize fuel/salt composition, concentrations of various isotopes and elements, and operational parameters throughout the reprocessing facility. Four primary measurement methodologies have been simulated based on either physical simulations or empirical correlations: gamma emissions, neutron emissions, hybrid k-edge densitometry (HKED), and cyclic voltammetry. Initial investigation into the use of these measures for process monitoring and detection suggests the approach is viable and worthy of further investigation. This report summarizes efforts to generate signatures of key measurements during operation of electrochemical reprocessing facilities and initial investigation of data analytics to support process monitoring, diversion detection, and accountancy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Trustworthiness modeling and evaluation for a nearly autonomous management and control system

The Nearly Autonomous Management and Control (NAMAC) system supports the advanced reactor operation by recommending control actions to operators based on real-time measurements and digital twins (DTs) learning from the knowledge base. To enable the safe and reliable use of autonomous technologies, NAMAC and its recommendations should be trustworthy to operators and regulators at both the design and operation stages. This study proposes a NAMAC trustworthiness modeling and evaluation framework supported by trustworthiness ontologies and evidence-based approaches. The development-time and run-time ontologies are separately constructed and then converted to Bayesian networks to quantitatively evaluate the NAMAC trustworthiness. This evaluation is demonstrated by collecting and characterizing evidence from NAMAC practices, such as the development and assessment of the NAMAC system, data coverage assessment, and the training and optimizations of neural-network-based DTs. Our proposed approach can aggregate various trustworthiness attributes of complex artificial-intelligence-supported systems for safety-critical applications. It also considers the interaction between different DTs and extends beyond the trustworthiness evaluation of a single DT. In conclusion, the evidence-based method enhances the transparency of the trustworthiness modeling and evaluation processes and helps identify uncertainties and subjectivity involved in the processes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Improved plutonium and americium photon branching ratios from microcalorimeter gamma spectroscopy

Photon branching ratios are critical input data for activities such as nuclear materials protection and accounting because they allow material compositions to be extracted from measurements of gamma-ray intensities. Uncertainties in these branching ratios are often a limiting source of uncertainty in composition determination. Here, we use high statistics, high resolution - (60–70 eV full-width-at-half-maximum at 100 keV) gamma-ray spectra acquired using microcalorimeter sensors to substantially reduce the uncertainties for 11 plutonium ( 238 Pu, 239 Pu, 241 Pu) and 241 Am branching ratios important for material control and accountability and nuclear forensics in the energy range of 125 keV to 208 keV. Lastly, we show a reduction in uncertainty of over a factor of three for one branching ratio and a factor of 2–3 for four branching ratios.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Uncertainty analysis for VERA problem 2 using the cell-code Condor v2.8.05

Condor is a cell-level neutronic calculation code that applies multi-group collision probabilities with heterogeneous response coupling method within generic geometry configurations. Under the Condor's code continuous development, the incorporation of up-to-date methodologies and state-of-the-art practices in reactor analysis represents a driving force. In this work, the capabilities of Condor v2.8.05 to develop an uncertainty analysis for realistic PWR-kind fuel assemblies are studied. The Total Monte Carlo approach is applied to quantify the impact of fabrication tolerances in the code's results for reactivity and power distributions, by means of randomly sampled input values using the VERA problem 2 as basis. The VERA problem 2 proposes a series of Westinghouse 2D 17 x 17-type fuel lattices, to be calculated reflected at beginning-of-life without Xe. The configurations correspond to a modern PWR. Selected neutronic parameters from Condor runs are thus analyzed in terms of the observed spread as well as the obtained distributions for the randomly perturbed cases, showing the capability of the code to handle the required input data, as well as its ability to provide valuable insights regarding uncertainty quantification.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Uncertainty about the Uncertainty [Slides]

A golden standard in science is to repeat an experiment a statistically significant number of times, recording data using the same set of detectors and the same data analysis methodology. In such case experimental error includes both the range of true values generated by repetitions of the experiment, and measurement uncertainty caused by the detector. They are independent. It is a huge and too frequently used simplification, to assume that one can measure multiple repetitions of an identical experiment, resulting in identical true experimental value. Repetitions, as similar is it is experimentally achievable result in a range of the true values rather than in a single value. When modern, very sensitive and well calibrated measurement systems are used, this range is not negligible, and sometimes dominates, in comparison to the measurement uncertainty. Range of true values depends on the physics of the experiment, while measurement uncertainty depends on the measurement method (properties of the detector not of the experiment). When data from one–of–a kind experiment are analyzed, only the measurement uncertainty is reported. It gives no information about the range, in which the true values of experiment would spread if the experiment was repeated. A frequently used approximation, that if a physical quantity is measured as a function of time, only measurement of this quantity, produces uncertainty is also in some real experiments fare to strong. Example: In reaction history time measurement uncertainty propagated to alpha dominated under certain conditions over the flux measurement uncertainty propagated to alpha. Reliability of a data point is in general independent from its measurement uncertainty. However, in practice reliable measurement methods frequently have high measurement uncertainty, while low reliability methods are applied to limit measurement uncertainty. Comparison of reliable data with high measurement uncertainty to not so reliable data measured with low uncertainty is discussed – in different scenarios different data analysis methods are applicable.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Energy Dependent Fission Product Yields

Since 2011, the LLNL-LANL-TUNL collaboration has undertaken experimental measurements of the energy evolution of the chain fission product yields (FPY) from neutron-induced fission of 235 U, 238 U, and 239 Pu using quasi-monoenergetic neutrons produced at the TUNL 10 MV Van de Graaff accelerator. Our method relies on direct, post-irradiation γ-ray spectroscopy of γ-rays emitted by fission products in actinide targets, with multiple γ-ray spectra taken continuously for a period from a half-hour to three months from the end of irradiation. The main experimental results of this study have been published for eight incident neutron energies of En = 0.58, 1.37, 2.37, 3.6, 4.6, 5.5, 8.9 and 14.8 MeV [1–4]. For each incident energy, approximately 16 cumulative FPYs were determined, nearly all being high-yield fission products, i.e., those occurring in the peaks of the mass distributions. As will be described in this report, our FPY analysis has been significantly improved in every step of the process, reducing the overall systematic uncertainties compared to previously published data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗